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This poster presents an overview of the equivalent test bed in PSCAD and PSLF for studying advanced power systems controller performance.
The Bayesian approach has been used for the dynamic state estimation (DSE) of a power system. However, due to the complexity of noise resources, it is difficult to quantify measurement and process noise using probability density functions (PDFs). To overcome the difficulty, the authors of this paper propose a modified eigen-decomposition-based interval analysis (MEDIA) method, which employs bounds instead of PDFs to quantify the noise, and uses the eigen decomposition method to reduce the negative impact of the overestimation problem. Using the simulation data generated from IEEE 16-machine and IEEE 10-machine systems, it is shown that the proposed MEDIA method can estimate the hard boundaries of dynamic states in real time. Furthermore, comparison with the forward-backward propagation method and the extended set-membership filter also shows that the proposed MEDIA method performs better by providing narrower boundaries in the DSE.
An integration study was performed by Rocketdyne under contract to NASA-LeRC. The study was concerned with coupling an SP-0100 reactor to either a Brayton or Stirling power conversion system. The application was for a surface power system to supply power requirements to a lunar base. A power level of 550 kWe was selected based on the NASA Space Exploration Initiative 90-day study. Reliability studies were initially performed to determine optimum power conversion redundancy. This study resulted in selecting three operating engines and one stand-by unit. Integration design studies indicated that either the Brayton or Stirling power conversion systems could be integrated with the PS-100 reactor. The Stirling system had an integration advantage because of smaller piping size and fewer components. The Stirling engine, however, is more complex and heavier than the Brayton rotating unit, which tends to off-set the Stirling integration advantage. From a performance consideration, the Brayton had a 9 percent mass advantage, and the Stirling had a 50 percent radiator advantage.
The design of a multihundred-watt Dynamic Isotope Power System (DIPS), based on the U.S. Department of Energy (DOE) General Purpose Heat Source (GPHS) and small (multihundred-watt) free-piston Stirling engine (FPSE), is being pursued as a potential lower cost alternative to radioisotope thermoelectric generators (RTG's). The design is targeted at the power needs of future unmanned deep space and planetary surface exploration missions ranging from scientific probes to Space Exploration Initiative precursor missions. Power level for these missions is less than a kilowatt. The incentive for any dynamic system is that it can save fuel and reduce costs and radiological hazard. Unlike DIPS based on turbomachinery conversion (e.g. Brayton), this small Stirling DIPS can be advantageously scaled to multihundred-watt unit size while preserving size and mass competitiveness with RTG's. Stirling conversion extends the competitive range for dynamic systems down to a few hundred watts--a power level not previously considered for dynamic systems. The challenge for Stirling conversion will be to demonstrate reliability and life similar to RTG experience. Since the competitive potential of FPSE as an isotope converter was first identified, work has focused on feasibility of directly integrating GPHS with the Stirling heater head. Thermal modeling of various radiatively coupled heat source/heater head geometries has been performed using data furnished by the developers of FPSE and GPHS. The analysis indicates that, for the 1050 K heater head configurations considered, GPHS fuel clad temperatures remain within acceptable operating limits. Based on these results, preliminary characterizations of multihundred-watt units have been established.
The analysis and integration studies of multimegawatt nuclear power conversion systems for potential SDI applications is presented. A study is summarized which considered 3 separate types of power conversion systems for steady state power generation with a duty requirement of 1 yr at full power. The systems considered are based on the following conversion cycles: direct and indirect Brayton gas turbine, direct and indirect liquid metal Rankine, and in core thermionic. A complete mass analysis was performed for each system at power levels ranging from 1 to 25 MWe for both heat pipe and liquid droplet radiator options. In the modeling of common subsystems, reactor and shield calculations were based on multiparameter correlation and an in-house analysis for the heat rejection and other subsystems.
With the worldwide growth in deploying high-voltage direct current (HVDC) transmission systems, their ability to facilitate black-start (BS) restoration has been a research topic of interest. In this context, voltage source converter (VSC)-HVDC is regarded as a BS resource, and this paper proposes a VSC-HVDC-assisted parallel BS restoration strategy in bulk power systems. The proposed strategy consists of two stages: 1) determination of the VSC and generator startup sequence and 2) load restoration simulation. In the first stage, the entire blackout system is sectionalized into multiple subsystems. Each subsystem includes a VSC-HVDC station or traditional BS unit, it independently determines its generator startup timeline and the energization timelines for buses and lines. The second stage involves load restoration, conceptualized as a modified unit commitment problem, with the timelines established in the first stage work as critical inputs. The proposed BS restoration strategy is tested on the San Diego power system to simulate the 2011 Southwest blackout. The simulation results validate the effectiveness of using VSC-HVDC links as a BS resource which not only speeds up the restoration process but also reduces both energy and economic losses.
Desigg and performance of SNAP-8 nuclear reactor simulator for nonnuclear testing of space power systems
An environmentally oriented microwave technology exploratory research program aimed at reducing the uncertainty associated with microwave power system critical technical issues is described. Topics discussed include: (1) Solar Power Satellite System (SPS) development plan elements; (2) critical technology issues related to the SPS preliminary reference configuration; (3) pilot plant to demonstrate commercial viability of the SPS system; and (4) research areas required to demonstrate feasibility of the SPS system. Progress in the development of advanced GaAs solar cells is reported along with a power distribution subsystem.
The dynamic isotope power systems (DIPS) demonstration program is focused on a standardized 2.5 kWe portable generator for multiple uses on the lunar or Martian surface. A variety of potential remote or mobile applications has been identified by NASA. These applications include remote power to science packages, surface rovers for both short and extended duration missions, and backup to central base power. Reviews conducted on alternative power sources for these applications are described. These include the comparison of DIPS to regenerative fuel cells (RFCs). Recent work is presented refining the 2.5 kWe design to assure compatibility with the Martian environment while imposing only a minor mass penalty on lunar operations. This was accomplished by limiting temperatures, except in the heat source unit (HSU), to the nonrefractory materials regime and protecting the necessary refractories in the HSU from the environment. Design changes to the HSU are described. Work related to recent concerns regarding astronaut radiation doses is described. This work includes the bases for the calculations to determine the necessary shielding or operational limitations.
In this paper, we propose a self-healing phasor measurement unit (PMU) network that exploits the features of dynamic and programmable configuration in a software-defined networking infrastructure to achieve resiliency against cyber-attacks. After a cyber-attack, the configuration of network switches is changed to isolate the compromised PMUs/phasor data concentrators to prevent further propagation of the attack; meanwhile, the disconnected yet uncompromised PMUs will be reconnected to the network to "self-heal" and thus restore the observability of the power system. Specifically, we formulate an integer linear programming model to minimize the overhead of the self-healing process (e.g., the recovery latency), while considering the constraints of power system observability, hardware resources, and network topology. We also propose a heuristic algorithm to decrease the computational complexity. Case studies of a PMU network based on the IEEE 30-bus and 118-bus systems are used to validate the effectiveness of the self-healing mechanism.
Grid resilience is a concept related to a power system's ability to continue operating and delivering power even in the event that low probability, high-consequence disruptions such as hurricanes, earthquakes, and cyber-attacks occur. Grid resilience objectives focus on managing and, ideally, minimizing potential consequences that occur as a result of these disruptions. Currently, no formal grid resilience definitions, metrics, or analysis methods have been universally accepted. This document describes an effort to develop and describe grid resilience metrics and analysis methods. The metrics and methods described herein extend upon the Resilience Analysis Process (RAP) developed by Watson et al. for the 2015 Quadrennial Energy Review. The extension allows for both outputs from system models and for historical data to serve as the basis for creating grid resilience metrics and informing grid resilience planning and response decision-making. This document describes the grid resilience metrics and analysis methods. Demonstration of the metrics and methods is shown through a set of illustrative use cases.
Through its Laboratory Directed Research and Development (LDRD) program, NREL is investigating how the resilience of the electric power system can be measured, evaluated, and visualized - ultimately to provide utilities, government agencies, and communities with tools that can help them prepare for a variety of unpredictable scenarios.
The Inflation Reduction Act of 2022 (IRA) and the Infrastructure Investment and Jobs Act of 2021, commonly referred to as the 'Bipartisan Infrastructure Law (BIL),' collectively represent the largest commitment of the U.S. Federal Government to invest in the modernization and decarbonization of the U.S. energy system. The Congressional Budget Office (CBO) estimates that total support for the broad range of climate and clean energy programs, tax credits, and other incentives authorized through the two laws will exceed $430 billion from 2022 through 2031 (CRS 2022; CBO 2021, 2022). While the climate and clean energy provisions are numerous and have the potential to impact all aspects of the U.S. energy system from fuel and electricity production to final consumption in industry, transportation, and buildings, the provisions relevant to the electricity sector - in particular the suite of tax credits for clean generation, storage, and carbon dioxide ( CO 2 ) capture and storage - are expected to be some of the most consequential in terms of emissions reduction and clean energy deployment (Larsen et al. 2022; Jenkins, Mayfield, et al. 2022; Mahajan et al. 2022; Zhao et al. 2022). In this report, we detail the methods and results of a study estimating the potential impacts of key provisions of IRA and BIL on the contiguous U.S. power sector from present day through 2030. The analysis employs an advanced power system planning model, the Regional Energy Deployment System (ReEDS), to evaluate how major provisions from both laws impact investment in and operation of utility-scale generation, storage, and transmission, and, in turn, how those changes impact power system costs, emissions, and climate and health damages. While not exhaustive in capturing every provision, the analysis estimates the possible scale of power-sector impacts that could result from the modeled provisions in IRA and BIL. The study is structured around two scenarios to evaluate the potential impacts of both laws on the power sector: 1) No New Policy: A counter-factual scenario that reflects all Federal and state policies enacted as of September 2022, with exception to IRA and BIL, and assumes load growth consistent with the Energy Information Administration's Annual Energy Outlook 2022 (AEO22) Reference case (EIA 2022a); 2) IRA-BIL: A scenario reflecting all Federal and state policies enacted as of September 2022, including key IRA and BIL provisions, most notably the investment and production tax credits for zero-carbon emitting electricity generation and storage (ITC and PTC), the tax credit for CO 2 capture and storage (45Q), and the tax credit for existing nuclear plants (described further in Section 2.3). To account for the impacts of IRA and BIL on electrification, assumes increased load growth consistent with a scaled version of the Medium Electrification scenario from the Electrification Futures Study (Mai et al. 2018). These scenarios are simulated across seven sets of assumptions with varying projected future electricity market conditions, including technology costs and performance, natural gas prices, and the degree of availability, feasibility, and cost of development of renewable resources, electricity transmission, and CO 2 pipeline, injection, and storage infrastructure. In addition, we simulate two sensitivities on the 'policy' treatment in which we vary key assumptions pertaining to the realized value of the clean electricity ITC and PTC: 1) the cost of monetization of tax credits, and 2) the level of bonus crediting realized by project developers. We demonstrate that IRA and BIL have the collective potential to drive substantial growth in clean electricity by 2030, while reducing costs for consumers, mitigating climate change, and decreasing the human health impacts of power sector emissions. However, we also demonstrate that if expected cost improvements of clean technologies are not realized and/or constraints on deployment driven by factors such as supply-chain challenges, regulatory hurdles, and the social acceptability of energy infrastructure development limit the rate of clean energy and associated infrastructure deployment (such as transmission), then the share of clean generation achieved and the associated emissions benefits realized may be substantively reduced.
Communication networks are integral to modern power grid operations and are becoming increasingly critical as grid dynamics speed up and as more controls become closed-loop in form. Focusing on the interdependence between the physical grid and the communication system, we identify several key characteristics and typical graph properties based on analysis of a real communication system for a power grid. Moreover, an automated process was provided for synthetic testbed in the NS-3 simulator for the power system test case, and its network characteristics have been further derived for power system monitoring and control applications
The energy sector is heavily dependent on surface water availability for reliable electricity generation. Power system operations are usually evaluated through system reliability and economic perspectives, with assumptions based on market prices and normal water availability. As natural gas technologies continue to dominate new thermal capacity, replacing retiring coal and nuclear generators, natural gas price stability becomes increasingly important and the impact of price volatility on grid operations must be understood. Here, we explore the range of Western Electricity Coordinating Council (WECC) regional power operations, which represents the electric interconnection over the western half of the continental United States, using a production cost model driven by different fuel prices and an integrated hydrology model to simulate historical water availability. Our results show system-wide operation costs increasing in drought years or when gas prices increase, as expected. In addition, we found those system-wide increases can be of the same magnitude. Regional analysis of the responses to compounded droughts and price volatility highlight differences in magnitude and direction depending on regional generation technology portfolios. The Pacific Northwest is most sensitive to drought conditions, Southern California is most sensitive to gas prices, and the Desert Southwest is sensitive to both with the same magnitude. This analysis motivates further research in combined hydrology and power system modeling to characterize regional dynamics and associated uncertainties across scales, which is an important underpinning for the development of more resilient energy and water systems.
Here this paper proposes a deep sigma point processes (DSPP)-assisted chance-constrained power system transient stability preventive control method to deal with uncertain renewable energy and loads-induced stability risk. The traditional transient stability-constrained preventive control is reformulated as a chance-constrained optimization problem. To deal with the computational bottleneck of the time-domain simulation-based probabilistic transient stability assessment, the DSPP is developed. DSPP is a parametric Bayesian approach that allows us to predict system transient stability with high computational efficiency while accurately quantifying the confidence intervals of the predictions that can be used to inform system instability risk. To this end, with a given preset confidence probability, we embed DSPP into the primal dual interior point method to help solve the chance-constrained preventive control problem, where the corresponding Jacobian and Hessian matrices are derived. Comparison results with other existing methods show that the proposed method can significantly speed up preventive control while maintaining high accuracy and convergence
The Nuclear Systems Kilopower Project was initiated by NASA's Space Technology Mission Directorate Game Changing Development Program in fiscal year 2015 to demonstrate subsystem-level technology readiness of small space fission power in a relevant environment (Technology Readiness Level 5) for space science and human exploration power needs. The Nuclear Systems Kilopower Project centerpiece is the Kilopower Reactor Using Stirling Technology (KRUSTY) test, which consists of the development and testing of a fission ground technology demonstrator of a 1 kWe-class fission power system. The technologies to be developed and validated by KRUSTY are extensible to space fission power systems from 1 to 10 kWe, which can enable higher power future potential deep space science missions, as well as modular surface fission power systems for exploration. The Kilopower Project is cofounded by NASA and the Department of Energy National Nuclear Security Administration (NNSA).KRUSTY include the reactor core, heat pipes to transfer the heat from the core to the power conversion system, and the power conversion system. Los Alamos National Laboratory leads the design of the reactor, and the Y-12 National Security Complex is fabricating it. NASA Glenn Research Center (GRC) has designed, built, and demonstrated the balance of plant heat transfer and power conversion portions of the KRUSTY experiment. NASA MSFC developed an electrical reactor simulator for non-nuclear testing, and the design of the reflector and shielding for nuclear testing. In 2016, an electrically heated non-fissionable Depleted Uranium (DU) core was tested at GRC in a configuration identical to the planned nuclear test. Once the reactor core has been fabricated and shipped to the Device Assembly Facility at the NNSAs Nevada National Security Site, the KRUSTY nuclear experiment will be assembled and tested. Completion of the KRUSTY experiment will validate the readiness of 1 to 10 kWe space fission technology for NASAs future requirements for sunlight-independent space power. An early opportunity for demonstration of In-Situ Resource Utilization (ISRU) capability on the surface of Mars is currently being considered for 2026 launch. Since a space fission system is the leading option for power generation for the first Mars human outpost, a smaller version of a planetary surface fission power system could be built to power the ISRU demonstration and ensure its end-to-end validity. Planning is underway to start the hardware development of this subscale flight demonstrator in 2018.
With the increasing penetration of distributed generators in the smart grids, having knowledge of rapid real-time electromechanical dynamic states has become crucial to system stability control. Conventional Supervisory Control and Data Acquisition (SCADA)-based dynamic state estimation (DSE) techniques are limited by the slow sampling rates, while the emerging phasor measurement units (PMUs) technology enables rapid real-time measurements at network nodes. Using generator bus terminal voltages, we propose a hybrid-learning DSE (HL-DSE) algorithm to estimate the synchronous machine rotor angle and speed in real time. The HL-DSE takes the power system model into account and trains neuroestimators with real-time data in an online manner. Compared with traditional DSE methods, the HL-DSE overcomes limitations by using a data-driven approach in conjunction with the physical power system model. The time efficiency, accuracy, convergence, and robustness of the proposed algorithm are tested under noises and fault conditions in both small- and large-scale test systems. Simulation results show that the proposed HL-DSE is much more computationally efficient than widely used Kalman filter (KF)-based methods while maintaining comparable accuracy and robustness. In particular, HL-DSE is over 100 times faster than square-root unscented KF (SR-UKF) and 80 times faster than extended KF (EKF). The advantages and challenges of the HL-DSE are also discussed.